Classification Criteria and Clinical Practice Guidelines for Rheumatic Diseases

Hassan, Rosline; Faruqui, Hanan; Alquraa, Reem; Eissa, Ayman; Alshaiki, Fatma; Cheikh, Mohamed

doi:10.1007/978-981-15-8323-0_25

Cited by 3 publications

(3 citation statements)

References 43 publications

(24 reference statements)

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“…In the feature selection process, we first identified all possible features of each of the disorders [25,40] and ensured that the features were clearly defined to avoid misdiagnosis. All the markers associated with each of the disorders were first identified followed by identification of the features that characterize each of the markers.…”

Section: Feature Selection and Processingmentioning

confidence: 99%

Diagnostic Tool for Early Detection of Rheumatic Disorders Using Machine Learning Algorithm and Predictive Models

Mills,

Dey,

Kassim

et al. 2024

BioMedInformatics

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Background: Rheumatic diseases are chronic diseases that affect joints, tendons, ligaments, bones, muscles, and other vital organs. Detection of rheumatic diseases is a complex process that requires careful analysis of heterogeneous content from clinical examinations, patient history, and laboratory investigations. Machine learning techniques have made it possible to integrate such techniques into the complex diagnostic process to identify inherent features that lead to disease formation, development, and progression for remedial measures. Methods: An automated diagnostic tool using a multilayer neural network computational engine is presented to detect rheumatic disorders and the type of underlying disorder for therapeutic strategies. Rheumatic disorders considered are rheumatoid arthritis, osteoarthritis, and systemic lupus erythematosus. The detection system was trained and tested using 70% and 30% respectively of labelled synthetic dataset of 100,000 records containing both single and multiple disorders. Results: The detection system was able to detect and predict underlying disorders with accuracy of 97.48%, sensitivity of 96.80%, and specificity of 97.50%. Conclusion: The good performance suggests that this solution is robust enough and can be implemented for screening patients for intervention measures. This is a much-needed solution in environments with limited specialists, as the solution promotes task-shifting from the specialist level to the primary healthcare physicians.

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Section: Feature Selection and Processingmentioning

confidence: 99%

Diagnostic Tool for Early Detection of Rheumatic Disorders Using Machine Learning Algorithm and Predictive Models

Mills,

Dey,

Kassim

et al. 2024

BioMedInformatics

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“…Arthritis is estimated to affect 53.2 million adults in the United States, with one in five people living with a diagnosis of arthritis ( 1 ). The most prevalent forms of arthritis include osteoarthritis, characterised by cartilage deterioration with a loss of joint space, and inflammatory arthritides (IA) such as rheumatoid arthritis (RA), spondyloarthritis, and gout ( 2 ). Although the pathogenesis of this latter group is diverse, IA have a chronic and progressive natural history that, if uncontrolled, may lead to irreversible joint damage ( 3 ).…”

Section: Introductionmentioning

confidence: 99%

The effectiveness and safety of lifestyle medicine and integrative therapies in inflammatory arthritis: an umbrella review using a hierarchical evidence gathering approach

Lin,

Liu,

O’Fee

et al. 2024

Front. Med.

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ObjectiveAn umbrella review was conducted to provide a comprehensive evaluation of the evidence on lifestyle medicine and integrative therapies for inflammatory arthritis.MethodsFive electronic databases were searched for umbrella reviews, meta-analyses, and systematic reviews of randomised controlled trials on acupuncture, diet, exercise, herbal medicine, nutrient supplements, and mind–body therapies for rheumatoid arthritis, spondyloarthritis, and gout published from January 2012 to December 2022. The primary outcomes were functional status and quality of life. Quality assessment was performed using the A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2) tool, and the certainty of evidence for our primary outcomes was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach where possible.ResultsWe included 52 reviews. Exercise was beneficial for functional status in both rheumatoid arthritis and spondyloarthritis, with moderate certainty of evidence. Chinese herbal medicine in combination with disease-modifying anti-rheumatic drugs may improve functional status in rheumatoid arthritis (very low certainty evidence). Acupuncture may improve functional status in rheumatoid arthritis and pain in both rheumatoid arthritis and gout; however, the evidence is of very low certainty. Evidence for other therapies was not clinically significant; however, it suggests possible benefits from quercetin and polyunsaturated fatty acids. Yoga may result in a moderate improvement in functional status when used as an adjunct to medication; however, the certainty of evidence is very low. Diet interventions offered inconsistent improvements to functional status in rheumatoid arthritis, spondyloarthritis, and gout with low to very low certainty.ConclusionExercise should be prescribed for people with rheumatoid arthritis and spondyloarthritis. More research is needed to confirm or refute evidence for Chinese herbal medicine, acupuncture, yoga, and anti-inflammatory diets.

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“…Irrespectively of the specific disease type, the affected organs are infiltrated by auto-reactive and activated immunocytes and their chemical products proinflammatory cytokines [ 5 ]. In autoimmune disorders, in addition to auto-activated lymphocytes, autoantibodies alone or in conjunction with circulating or tissue autoantigens, along with activation of type I interferon pathways are prevalent [ [6] , [7] , [8] ].…”

Section: Introductionmentioning

confidence: 99%

Autoimmune rheumatic diseases: One or many diseases?

Moutsopoulos

2021

Journal of Translational Autoimmunity

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Until the etiopathogenic factor(s) of autoimmune and autoinflammatory rheumatic disorders will be identified, their classification into entities will continue. However, their similar clinical manifestations, overlapping syndromes, evolution from one entity into another, as well as common autoantibody responses, suggest that autoimmune and autoinflammatory disorders may constitute distinct pathophysiologic processes on the basis of a different genetic background. Prognosis and effective therapeutic regimens are mostly based on the clinico-pathologic severity of the involved tissues or organs and not on the disease label.

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Classification Criteria and Clinical Practice Guidelines for Rheumatic Diseases

Cited by 3 publications

References 43 publications

Diagnostic Tool for Early Detection of Rheumatic Disorders Using Machine Learning Algorithm and Predictive Models

Diagnostic Tool for Early Detection of Rheumatic Disorders Using Machine Learning Algorithm and Predictive Models

The effectiveness and safety of lifestyle medicine and integrative therapies in inflammatory arthritis: an umbrella review using a hierarchical evidence gathering approach

Autoimmune rheumatic diseases: One or many diseases?

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